ReviewBMC genomics2015
Computational methods and resources for the interpretation of genomic variants in cancer.
Review in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 30 citations in OpenAlex.
- The role of Gln269Leu mutation on the thermostability and structure of uricase from Aspergillus flavus.Scientific reports · 2025Article
- Vaccine-induced T cell receptor T cell therapy targeting a glioblastoma stemness antigen.Nature communications · 2025Article
- Identification of Driver Epistatic Gene Pairs Combining Germline and Somatic Mutations in Cancer.International journal of molecular sciences · 2023Article
- Article
- Prostate cancer in omics era.Cancer cell international · 2022Article
- A conjoined universal helper epitope can unveil antitumor effects of a neoantigen vaccine targeting an MHC class I-restricted neoepitope.NPJ vaccines · 2021Article
- Review on the Computational Genome Annotation of Sequences Obtained by Next-Generation Sequencing.Biology · 2020Review
- Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine.Computational and structural biotechnology journal · 2020Review
- Genomic analysis of pancreatic juice DNA assesses malignant risk of intraductal papillary mucinous neoplasm of pancreas.Cancer medicine · 2019Article
- Integrating molecular networks with genetic variant interpretation for precision medicine.Wiley interdisciplinary reviews. Systems biology and medicine · 2019Review
- Visual Analytics of Genomic and Cancer Data: A Systematic Review.Cancer informatics · 2019Review
- Novel putative drivers revealed by targeted exome sequencing of advanced solid tumors.PloS one · 2018Article
- Spatial distribution of disease-associated variants in three-dimensional structures of protein complexes.Oncogenesis · 2017Article
- VarI-SIG 2015: methods for personalized medicine - the role of variant interpretation in research and diagnostics.BMC genomics · 2016Article
- PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions.PLoS computational biology · 2016Article
- VarI-SIG 2014--From SNPs to variants: interpreting different types of genetic variants.BMC genomics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The recent improvement of the high-throughput sequencing technologies is having a strong impact on the detection of genetic variations associated with cancer. Several institutions worldwide have been sequencing the whole exomes and or genomes of cancer patients in the thousands, thereby providing an invaluable collection of new somatic mutations in different cancer types. These initiatives promoted the development of methods and tools for the analysis of cancer genomes that are aimed at studying the relationship between genotype and phenotype in cancer. In this article we review the online resources and computational tools for the analysis of cancer genome. First, we describe the available repositories of cancer genome data. Next, we provide an overview of the methods for the detection of genetic variation and computational tools for the prioritization of cancer related genes and causative somatic variations. Finally, we discuss the future perspectives in cancer genomics focusing on the impact of computational methods and quantitative approaches for defining personalized strategies to improve the diagnosis and treatment of cancer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.